The design of renewable support schemes and CO2 emissions in China

Abstract The renewable energy targets put forward by the Chinese government need comprehensive incentive schemes. This paper uses a multi-regional CGE model to evaluate two types of renewable support schemes; a subsidy scheme like a feed-in tariff (FIT) with a direct price impact for final consumers and a subsidy scheme without any price impact. We assess the CO 2 consequences of both approaches, as well as their impact on economic activity in terms of GDP, industrial structure, electricity generation structure, and regional final demand elasticities of electricity. We find that a support scheme with price impact is much more effective in reducing CO 2 emissions while the difference in GDP between the two policies is small. We estimate that the price implications of the support scheme allow for an additional emissions reduction of 113 Mt CO 2 —or 0.07% of total emissions—in China during 2020–2035. The support scheme with a price impact does not lead to a negative impact on the Chinese economy although there are significant differences among regions. In addition, while the whole country faces an approximately unitary electricity elasticity demand, we find significant differences in electricity demand elasticities among Chinese regions.

[1]  Interactions of emission caps and renewable electricity support schemes , 2015 .

[2]  Y. Gagnon,et al.  An analysis of feed-in tariff remuneration models: Implications for renewable energy investment , 2010 .

[3]  J. Lesser,et al.  Design of an economically efficient feed-in tariff structure for renewable energy development , 2008 .

[4]  J. Albrecht,et al.  Balancing demand-pull and supply-push measures to support renewable electricity in Europe , 2015 .

[6]  Ying Fan,et al.  How will a nationwide carbon market affect regional economies and efficiency of CO2 emission reduction in China , 2016 .

[7]  P. Eng CO2 emissions from fuel combustion: highlights , 2009 .

[8]  Rashid Alammari,et al.  Review of policies encouraging renewable energy integration & best practices , 2015 .

[9]  Boqiang Lin,et al.  Levelized cost of electricity (LCOE) of renewable energies and required subsidies in China , 2014 .

[10]  Ying Fan,et al.  The Economic Effects of Initial Quota Allocations on Carbon Emissions Trading in China , 2016 .

[11]  Zifa Liu,et al.  The Economics of Wind Power in China and Policy Implications , 2015 .

[12]  Helena Martín,et al.  Evaluating the approach to reduce the overrun cost of grid connected PV systems for the Spanish electricity sector: Performance analysis of the period 2010–2012 , 2014 .

[13]  Jiyong Kim,et al.  Feasibility and impact analysis of a renewable energy source (RES)-based energy system in Korea , 2015 .

[14]  Yongxiu He,et al.  Feed-in tariff mechanisms for large-scale wind power in China , 2015 .

[15]  R. Haas,et al.  Fixed feed-in tariff versus premium: A review of the current Spanish system , 2012 .

[16]  O. Langniss,et al.  Advanced Mechanisms for the Promotion of Renewable Energy: Models for the Future Evolution of the German Renewable Energy Act , 2008 .

[17]  Paul Dargusch,et al.  The cost-effectiveness of household photovoltaic systems in reducing greenhouse gas emissions in Australia: Linking subsidies with emission reductions , 2015 .

[18]  Pablo del Río,et al.  The dynamic efficiency of feed-in tariffs: The impact of different design elements , 2012 .

[19]  M. Thring World Energy Outlook , 1977 .